On-site activities are typically performed when the end-product is immovable once it has been assembled and/or due to weight and space constraints in the production and transportation system. It is primarily a customer order driven type of production with a high level of customization. However, some customer order driven and/or customization activities can, or should, be performed off-site, but these aspects are typically treated in isolation of each other. There is therefore a need to make a combined assessment of on-site activities, customer order driven production, and customization activities. The purpose of this paper is thus to develop a typology that provides a holistic view of on-site activities in relation to customer order driven and customization activities. A flow-based three-dimensional typology is developed to assess combinations of three dimensions: flow driver, flow differentiation, and flow location. The property of each dimension is determined using decoupling points. The typology represents how on-site activities impact the feasibility of customer order driven and customization activities. “On-site” is defined as pursuing activities at the site where the final delivery is made. The findings show that forecast driven activities are risky to perform on-site and these should instead be performed before delivery to the site (off-site). The typology is applied to three case companies to illustrate its applicability to building construction. Future studies should extend the typology application to other types of construction and ETO industries to enable benchmarking of site-based production to other contexts with similar challenges related to on-site/off-site production.

This paper provides a systematic literature review of Sales and Operations Planning (S&OP) in process industries. The aim is to investigate the present state of S&OP in process industries in comparison to discrete manufacturing industries and to identify the desired future state of the S&OP process based on the specific characteristics of process industries. The findings of this paper show that this issue has not received much attention in the academic world. Hence there is a need for conceptual models with focus on process industries’ specific characteristics. Process industries are actually hybrids of continuous production and discrete production (respectively, upstream and downstream of the discretization point) and the specific characteristics of process industries are related to the continuous production part. Thus, in this paper, the characteristics upstream of the discretization point are investigated and the integration of them in the S&OP process of the process industries is stressed.

There is a need to identify and categorise different types of nonlinearities that commonly appear in supply chain dynamics models, as well as establishing suitable methods for linearising and analysing each type of nonlinearity. In this paper simplification methods to reduce model complexity and to assist in gaining system dynamics insights are suggested. Hence, an outcome is the development of more accurate simplified linear representations of complex nonlinear supply chain models. We use the highly cited Forrester production-distribution model as a benchmark supply chain system to study nonlinear control structures and apply appropriate analytical control theory methods. We then compare performances of the linearised model with numerical solutions of the original nonlinear model and with other previous research on the same model. Findings suggest that more accurate linear approximations can be found. These simplified and linearised models enhance the understanding of the system dynamics and transient responses, especially for inventory and shipment responses. A systematic method is provided for the rigorous analysis and design of nonlinear supply chain dynamics models, especially when overly simplistic linear relationship assumptions are not possible or appropriate. This is a precursor to robust control system optimisation. (C) 2015 Elsevier B.V. All rights reserved.

The integration of scheduling and control in the process industry is a topic that has been frequently discussed during the recent years, but many challenges remain in order to achieve integrated solutions that can be implemented for large-scale industrial sites. In this paper we consider production control under disturbances in the supply of utilities at integrated sites together with the integration towards production scheduling. Utilities, such as steam and cooling water, are often shared between the production areas of a site, which enables formulation of an optimization problem for determining the optimal supply of utilities to each area at the occurrence of a disturbance. Optimization in two timescales is suggested to handle the scheduling and disturbance management problems in a hierarchical fashion. The suggested structure has been discussed with companies within the chemical process industry. A simple example is provided to show how the structure may be used

There is no consensus on the supply chain management definition of resilience. To aid in evaluating the dynamic behaviour of such systems we need to establish clearly elucidated performance criteria that encapsulate the attributes of resilience. A literature review establishes the latter as readiness, responsiveness and recovery. We also identify robustness as a necessary condition that would complement resilience. We find that the Integral of the Time Absolute Error (ITAE) is an appropriate control engineering measure of resilience when it is applied to inventory levels and shipment rates. We use the ITAE to evaluate an often used benchmark model of make-to-stock supply chains consisting of three decision parameters. We use both linear and nonlinear forms of the model in our evaluation. Our findings suggest that optimum solutions for resilience do not yield a system that is robust to uncertainties in lead-time. Hence supply chains will experience drastic changes in their resilience performance when lead-time changes.

This paper shows the impact of using the net present value (NPV) on parameter selection in the ordering policy of a production planning and control system. Using a well understood and documented model, the net present value is used as an objective function to determine the discounted future variance costs resulting from the model's dynamics. The NPV of the variance (NPVv) is defined and applied to the model under make-to-order and make-to-stock conditions. We show that the cost structure of the manufacturing system defines the NPVv and hence aids in identifying the most appropriate control strategy to apply. © 2005 Elsevier Ltd. All rights reserved.

Purpose - To provide an overview of how a number of frequently used smoothing-based forecasting techniques can be modelled for use in dynamic analysis of production-inventory systems. Design/methodology/approach - The smoothing techniques are modelled using transfer functions and state space representation. Basic control theory is used for analysing the dynamic properties. Findings - A set of expressions are derived for the smoothing techniques and dynamic properties are identified. Practical implications - Dynamic properties are important in many applications. It is shown that the different smoothing techniques can have very different influences on the dynamic behaviour and therefore should be considered as a factor when smoothing parameters are decided on. Originality/value - Dynamic behaviour of production-inventory systems can be analysed using control theory based on, e.g. transfer functions or state space models. In this paper a set of models for five common smoothing techniques are analysed and their respective dynamic properties are highlighted. © Emerald Group Publishing Limited.

All value chains are not designed the same way. A major determinant is the type of product that is to be supplied through the chain or network, calling for different types of value chains. An interesting model for this selection is the one developed by Fisher, arguing that products can be characterised as being either functional or innovative, and that supply chains are either physically efficient or market-responsive. Certain combinations of products and supply chains are assumed to provide matches whereas other combinations lead to mismatches. This paper combines this approach with the concept of a customer order decoupling point. We distinguish between a product supply decoupling point and a demand mediation decoupling point. A decoupling point divides the value chain into two distinct parts, one upstream with certain characteristics and one downstream with distinctly different characteristics. In this paper we specifically explore how the Fisher model can be used to characterise the role and features of upstream versus downstream value chain operations relative to the product supply decoupling point and the demand mediation decoupling point. Copyright © 2006 Inderscience Enterprises Ltd.

Purpose - A production-inventory system based on a model proposed by Axsäter is examined with the purpose of understanding the dynamic properties of the model. Design/methodology/approach - The information flow concept is discussed and a dynamic analysis using a system simplification approach is carried out to achieve an understanding of the dynamic behaviour of the system. Finally, the information flow is examined and analysed from a hierarchical perspective. Findings - The model is extended to include an order decision rule and a production unit and it is shown that the extended model has the capability to represent the dynamics of a number of different system management principles. The three different model instances of base stock, kanban and material requirements planning character are analysed. Originality/value - Dynamic modelling of production-inventory and supply chain models are usually analysed at an aggregate level not involving any complex relations of materials or capacities. In this paper, this line of research is merged with an approach based on multiple information channels using matrix representation and it is shown how a system simplification approach can be used for this purpose. © Emerald Group Publishing Limited.